Professor Mahmoud Kamel
The arrival of artificial intelligence is changing many professions, and translation is certainly one of them. But perhaps the more important question today is not whether artificial intelligence will replace translators. The real question is: What kind of translator will be needed in the age of AI?
This is the main question discussed in the second chapter of Translation Studies in the Age of Artificial Intelligence, edited by Sanjun Sun, Kanglong Liu and Riccardo Moratto. The chapter, written by Sanjun Sun and Ricardo Muñoz Martín, is entitled “Reframing Translation Expertise for the AI Era.” The authors try to understand how the skills needed by translators have changed and what translation education should do in response to these changes.
The translator is changing
For many years, the good translator was mainly expected to have excellent knowledge of two or more languages. This is still very important, but it is no longer enough.
A professional translator today works in a very different environment. Computers, translation memories, terminology databases, online resources and machine translation have already become part of the profession. Now, with generative AI and large language models such as ChatGPT, the change is becoming even faster.
This does not mean that language skills have become less important. On the contrary, they remain at the heart of translation. But translators now need additional abilities to work effectively with technology and to deal with a changing translation market.
The authors make an interesting comparison between two periods. They examine a Spanish survey conducted in 2004 and compare it with a Chinese survey conducted in 2024. The two studies were carried out in very different countries and at different times, but together they provide an opportunity to see how the idea of translation expertise has changed over twenty years.
From language skills to a wider set of skills
One important finding is that translation expertise today is not limited to language competence.
The study identifies 12 important areas of abilities, skills and knowledge for translators. These include language proficiency, knowledge of the subject or field, technological skills and professional soft skills. The results show that technology has become an important part of professional translation, but it has not removed the need for human expertise.
This is an important point.
A translator may use AI to produce a first draft in a few seconds. But someone still has to decide whether that draft is correct. Someone has to recognise a wrong meaning, a cultural problem, an unsuitable expression or a terminology mistake.
The machine can produce an answer.
The translator has to decide whether the answer should be trusted.
This may become one of the most important skills of the future translator.
The human factor
The chapter also makes a useful distinction between translation competence and translation expertise.
Competence can be understood as the knowledge and abilities that translators are expected to have. Expertise is more connected with how skilled translators actually work and how they solve problems in real situations.
This distinction is important in the age of AI because translation is becoming more complex. A translator may need to decide not only how to translate a sentence, but also whether AI should be used, which AI tool is appropriate, how its output should be checked, and when the machine should not be trusted.
In other words, the future translator will need professional judgment as much as technical knowledge.
What should universities do?
This brings us to an important question for universities.
Can we continue teaching translation in exactly the same way that we taught it twenty or thirty years ago?
Probably not.
Translation programmes need to give students strong language and cultural skills, but they also need to prepare them for the technological side of the profession. Students should learn how AI works, how to use it, how to evaluate its output and how to recognise its limitations.
At the same time, universities should not turn translation education into a simple course in using AI tools.
The purpose of translation education is still to produce professionals who understand language, culture, communication and the responsibility involved in transferring meaning from one language to another.
AI should be added to this education, not placed in its centre.
A new kind of translator
The translation profession has always changed with technology. The computer did not eliminate translators. The internet did not eliminate them. Computer-assisted translation did not eliminate them.
AI is more powerful than these earlier technologies, and its impact will probably be greater. Some routine translation work may become less common. At the same time, new roles are already developing in areas such as localisation, transcreation, cultural mediation and other forms of multilingual communication. Human expertise remains especially important in areas where cultural understanding, creativity and professional judgment are needed.
So, the translator of the future may not look exactly like the translator of the past.
He or she may spend less time translating every sentence from the beginning and more time reviewing, editing, managing terminology, checking quality and making important decisions.
This does not make the translator less important.
It may make the translator more responsible.
The real challenge is, therefore, not to compete with the machine in producing words faster. A machine will almost certainly win that competition.
The human translator must offer what the machine cannot easily provide: understanding of people, cultures, situations, intentions and responsibility.
The question is no longer:
“Will AI replace translators?”
The better question is:
“What kind of translator will AI require us to become?”
And perhaps the answer is simple: a translator who knows languages, understands people, uses technology wisely and knows when not to trust it.
By Dr Mahmoud Kamel
Professor at the Academy of Arts
